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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 170  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
HIP, ITE-HI, ASJ-H, VRPSY [detail] 2022-02-28
13:30
Online Online [Invited Talk] Glossiness perception -- cues, reproduction methods using 3D images and quantitative evaluation, brain mechanism, and effects on facial attractiveness and the neural correlates --
Yuichi Sakano (NICT/Osaka Univ.) HIP2021-70
By virtue of the recent great advances in computer graphics technology, mechanisms for the perception of object material... [more] HIP2021-70
pp.62-67
MI 2022-01-27
16:13
Online Online [Short Paper] utomatic Extraction of Regions of Vascular Lesions Including Diffuse Lesions in MR Images Using Weakly Supervised Deep Learning
Koki Fukaya, Takeshi Hara (Gifu Univ.), Taiki Nozaki, Masaki Matsusako (St.Luke's International Hosp.), Tetsuro Katafuchi (Gifu Medical Univ.), Xiangrong Zhou, Hiroshi Fujita (Gifu Univ.) MI2021-87
Klippel-Trenaunay-Weber syndrome (KTS) is a type of vascular lesion for which there is no quantitative diagnostic method... [more] MI2021-87
pp.186-187
IE 2022-01-24
13:05
Tokyo National Institute of Informatics
(Primary: On-site, Secondary: Online)
Reduction of Truncation Artifacts by Massive-Training Artificial Neural Network (MTANN) in Fast-Acquisition MRI of the Knee
Maodong Xiang, Ze Jin, Kenji Suzuki (Tokyo Tech) IE2021-31
MRI has a relatively long acquisition time, leading to patient comfort problems and artifacts from patient motion. Accel... [more] IE2021-31
pp.21-26
MI 2021-07-09
14:30
Online Online Asynchrony analysis of diaphragmatic movement for evaluation of respiratory dynamics in COPD patients
Xiao Tan (Chiba Univ.), Yuma Iwao (QST), Chen Ye, Kotaro Takahashi (Chiba Univ.), Yoshitada Masuda (Chiba Univ. Hospital), Ayako Shimada, Naoko Kawata, Hideaki Haneishi (Chiba Univ.) MI2021-20
The state of lung movement is an important index for the diagnosis of the chronic obstructive pulmonary disease (COPD). ... [more] MI2021-20
pp.47-51
MI 2021-05-17
10:00
Online Online [Short Paper] Regression of Induced Electric Field for TMS by using Neural Network and Governing Equation
Toyohiro Maki (NITech), Yoshikazu Ugawa, Takenobu Murakami (Fukushima Medical Univ.), Tatsuya Yokota, Akimasa Hirata, Hidekata Hontani (NITech) MI2021-1
TMS (Transcranial Magnetic Stimulation) is a method which stimulate the neurons in the brain by using a coil. Since stim... [more] MI2021-1
pp.1-2
MI 2021-05-17
14:40
Online Online MR super-resolution based on signal-image domain learning using phase scrambling Fourier transform imaging
Kazuki Yamato, Hiromichi Wakatsuki, Satoshi Ito (Utsunomiya Univ.) MI2021-6
In the phase-scrambling Fourier transform (PSFT) imaging, the signals not sampled during imaging can be extrapolated and... [more] MI2021-6
pp.14-19
MI 2021-03-15
15:15
Online Online Deep State-Space Modeling of FMRI Images with Disentangle Attributes
Koki Kusano (Kobe Univ.), Takashi Matsubara (Osaka Univ.), Kuniaki Uehara (Osaka Gakuin Univ.) MI2020-59
As well as the disorder and other targets, nuisance attributes such as age, gender, and scanner specifications underlie ... [more] MI2020-59
pp.56-61
MI 2021-03-15
15:45
Online Online Feasibility study of automatic extraction method of coronary artery stationary period using CNN -- Comparison between 1.5T and 3.0T --
Remina Kasai, Yuta Endo, Haruna Shibou, Makoto Amanuma, Kuninori Kobayashi, Shigehide Kuhara (Kyorin Univ.) MI2020-61
Magnetic resonance coronary angiography (MRCA) requires data acquisition during the stationary period of the coronary ar... [more] MI2020-61
pp.66-70
PRMU 2020-10-09
11:00
Online Online Examination of data preprocessing in functional MRI image analysis using CNN
Yuta Hosoi (Niigata Univ.), Takafumi Hayashi (Nihon Univ) PRMU2020-22
fuctional MRI(fMRI) has been used in various fields from medicine and neuroscience to psychology andlinguistics since it... [more] PRMU2020-22
pp.20-25
MI 2020-09-03
14:55
Online Online Performance Improvement of Alzheimer's Disease Classification Using Convolutional Neural Network
Daiki Endo, Koichi Ito, Takafumi Aoki (Tohoku Univ.) MI2020-31
Alzheimer's disease (AD) is a progressive brain disease that causes a different pattern of brain atrophy from normal agi... [more] MI2020-31
pp.63-67
IBISML 2020-03-11
14:10
Kyoto Kyoto University
(Cancelled but technical report was issued)
Accuracy of Brain Tumor Detection and Classification Based on Under Sampled k-Space Signals
Tania Sultana, Sho Kurosaki, Yutaka Jitsumatsu, Junichi Takeuchi (Kyushu Univ.) IBISML2019-46
The prime concern of Magnetic Resonance Imaging (MRI) is to optimize
examination time by assuring a good quality of the... [more]
IBISML2019-46
pp.91-94
IE, IMQ, MVE, CQ
(Joint) [detail]
2020-03-05
11:10
Fukuoka Kyushu Institute of Technology
(Cancelled but technical report was issued)
Human Motion Recognition from Single Camera Images Using TMRI
Cao Jing, Youtaro Yamashita, Joo Kooi Tan (Kyutech) IMQ2019-17 IE2019-99 MVE2019-38
In recent years, research on computer vision has progressed and is being applied in a wide range of fields. Among them, ... [more] IMQ2019-17 IE2019-99 MVE2019-38
pp.17-21
ITE-HI, IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] 2020-02-27
14:55
Hokkaido Hokkaido Univ.
(Cancelled but technical report was issued)
A Note on Estimation of Image Categories Using Brain Activity While Viewing Images Based on MVBGM-MS
Yusuke Akamatsu (Hokkaido Univ.), Ryosuke Harakawa (Nagaoka Univ. of Tech.), Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
This paper presents multi-view Bayesian generative model for multi-subject fMRI data (MVBGM-MS) for accurate estimation ... [more]
MI 2020-01-29
14:00
Okinawa OKINAWAKEN SEINENKAIKAN Effects of skull and surrounding area in functional MRI analysis using Convolutional Neural Network
Yuta Hosoi, Takafumi Hayashi (Niigata Univ.) MI2019-86
A fuctional MRI(fMRI) has been used in various fields from medicine and neuroscience to psychology andlinguistics since ... [more] MI2019-86
pp.91-96
SP 2020-01-28
15:50
Toyama   Measurement of momentum change in joint range using high-speed rtMRI movie
Takuya Asai, Hideaki Kikuchi (Waseda University), Kikuo Maekawa (NINJAL) SP2019-44
In our project, a database of the real-time magnetic resonance images (rtMRI) is constructed from FY 2017. It is difficu... [more] SP2019-44
pp.1-6
EMCJ, MW, EST, IEE-EMC [detail] 2019-10-25
15:05
Miyagi Tohoku Gakuin University(Conf. Room 2, Eng. Bldg. 1) Modeling Nerve Activation During TMS Targeting Language Area
Takashi Sakai (NITech), Keisuike Tani, Satoshi Tnaka (Hamamatsu Univ. School of Medicine), Akimasa Hirata (NITech) EMCJ2019-65 MW2019-94 EST2019-73
In recent years, there has been a growing interest in non-invasive stimulation of the brain for medical treatment and di... [more] EMCJ2019-65 MW2019-94 EST2019-73
pp.163-168
MBE, NC 2019-10-11
16:20
Miyagi   Selection of ultrasmall superparamagnetic particles of iron oxide for vessel size imaging
Kazuhiro Nakamura (Akita Noken), Norihiro Katayama (Tohoku Univ), Minoru Osanai (Osaka Univ), Toshibumi Kinoshita (Akita Noken) MBE2019-36 NC2019-27
Vessel size imaging (VSI) was already reported based on transverse relaxation time images obtained from spin echo and gr... [more] MBE2019-36 NC2019-27
pp.37-40
MI 2019-07-05
14:00
Hokkaido Future Univ. Hakodate [Short Paper] Automated extraction of cartilage regions on knee MR images by deep learning approach
Koki Fukaya, Takeshi Hara, Xiangrong Zhou (Gifu Univ.), Taiki Nozaki, Masaki Matsusako (St. Luke's HP), Hiroshu Fujita (Gifu Univ.) MI2019-17
(To be available after the conference date) [more] MI2019-17
pp.1-2
MBE 2019-05-19
09:50
Niigata Niigata University Quantitative evaluation of the femoral condylar shape in the knee joint with the discoid meniscus
Takeru Hirano, Toyohiko Hayashi (Niigata Univ), Satoshi Watanabe (Niigata Medical Center) MBE2019-3
In order to reduce the load working on the knee joint, two meniscuses are placed as soft tissue on the lateral and media... [more] MBE2019-3
pp.13-18
MI 2019-01-22
13:20
Okinawa   [Short Paper] Differences of Segmentation Results by Three Training Data for Cartilage Extraction in Knee MR Images Using Deep Learning
Ryoma Aoki, Takeshi Hara (Gifu Univ), Taiki Nozaki, Masaki Matsusako (Dept.of Radiol.,St.Luke's Hosp.), Xiangrong Zhou, Hiroshi Fujita (Gifu Univ) MI2018-76
Accurate grasp of cartilage area is important for diagnosis and treatment related to arthropathy diseases. In recent yea... [more] MI2018-76
pp.63-64
 Results 1 - 20 of 170  /  [Next]  
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